Lipidomics studies reveal dynamic changes in polar lipids of developing endosperm of oat and wheat varieties with differing oil contents.

Polar lipids have biosynthetic pathways which intersect and overlap with triacylglycerol biosynthesis; however, polar lipids have not been well characterized in the developing endosperms of oat with high oil accumulation. The polar lipids in endosperms of oat and wheat varieties having different oil contents were analyzed and compared at different developmental stages. Our study shows that the relative contents of polar lipid by mass were decreased more slowly in wheat than in oat. Phosphatidylcholine and phosphatidylethanolamine were the major phospholipids, which showed similar abundance and gradual decreases during endosperm development in oat and wheat, while lysophospholipids were noticeably higher in oat. Monogalactosyldiacylglycerol showed a gradual increase in wheat and a decrease in oat during endosperm development. The relative contents of some polar lipid species and their unsaturation index were significantly different in their endosperms. These characteristics of polar lipids might indicate an adaption of oat to accommodate oil accumulation.

Association of changes in expression of HDAC and SIRT genes after drug treatment with cancer cell line sensitivity to kinase inhibitors.

Histone deacetylases (HDACs) and sirtuins (SIRTs) are important epigenetic regulators of cancer pathways. There is a limited understanding of how transcriptional regulation of their genes is affected by chemotherapeutic agents, and how such transcriptional changes affect tumour sensitivity to drug treatment. We investigated the concerted transcriptional response of HDAC and SIRT genes to 15 approved antitumor agents in the NCI-60 cancer cell line panel. Antitumor agents with diverse mechanisms of action induced upregulation or downregulation of multiple HDAC and SIRT genes. HDAC5 was upregulated by dasatinib and erlotinib in the majority of the cell lines. Tumour cell line sensitivity to kinase inhibitors was associated with upregulation of HDAC5, HDAC1, and several SIRT genes. We confirmed changes in HDAC and SIRT expression in independent datasets. We also experimentally validated the upregulation of HDAC5 mRNA and protein expression by dasatinib in the highly sensitive IGROV1 cell line. HDAC5 was not upregulated in the UACC-257 cell line resistant to dasatinib. The effects of cancer drug treatment on expression of HDAC and SIRT genes may influence chemosensitivity and may need to be considered during chemotherapy.

Quantitative Investigation of FAD2 Cosuppression Reveals RDR6-Dependent and RDR6-Independent Gene Silencing Pathways.

The frequency and extent of transgene-mediated cosuppression varies substantially among plant genes. However, the underlying mechanisms leading to strong cosuppression have received little attention. In previous studies, we showed that the expression of FAD2 in the seeds of Arabidopsis results in strong RDR6-mediated cosuppression, where both endogenous and transgenic FAD2 were silenced. Here, the FAD2 strong cosuppression system was quantitatively investigated to identify the genetic factors by the expression of FAD2 in their mutants. The involvement of DCL2, DCL4, AGO1, and EIN5 was first confirmed in FAD2 cosuppression. SKI2, a remover of 3' end aberrant RNAs, was newly identified as being involved in the cosuppression, while DCL3 was identified as antagonistic to DCL2 and DCL3. FAD2 cosuppression was markedly reduced in dcl2, dcl4, and ago1. The existence of an RDR6-independent cosuppression was revealed for the first time, which was demonstrated by weak gene silencing in rdr6 ein5 ski2. Further investigation of FAD2 cosuppression may unveil unknown genetic factor(s).

Revisiting Concurrent Radiation Therapy, Temozolomide, and the Histone Deacetylase Inhibitor Valproic Acid for Patients with Glioblastoma-Proteomic Alteration and Comparison Analysis with the Standard-of-Care Chemoirradiation.

BACKGROUND: Glioblastoma (GBM) is the most common brain tumor with an overall survival (OS) of less than 30% at two years. Valproic acid (VPA) demonstrated survival benefits documented in retrospective and prospective trials, when used in combination with chemo-radiotherapy (CRT). PURPOSE: The primary goal of this study was to examine if the differential alteration in proteomic expression pre vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA as compared to standard-of-care CRT. The second goal was to explore the associations between the proteomic alterations in response to VPA/RT/TMZ correlated to patient outcomes. The third goal was to use the proteomic profile to determine the mechanism of action of VPA in this setting. MATERIALS AND METHODS: Serum obtained pre- and post-CRT was analyzed using an aptamer-based SOMAScan® proteomic assay. Twenty-nine patients received CRT plus VPA, and 53 patients received CRT alone. Clinical data were obtained via a database and chart review. Tests for differences in protein expression changes between radiation therapy (RT) with or without VPA were conducted for individual proteins using two-sided t-tests, considering p-values of <0.05 as significant. Adjustment for age, sex, and other clinical covariates and hierarchical clustering of significant differentially expressed proteins was carried out, and Gene Set Enrichment analyses were performed using the Hallmark gene sets. Univariate Cox proportional hazards models were used to test the individual protein expression changes for an association with survival. The lasso Cox regression method and 10-fold cross-validation were employed to test the combinations of expression changes of proteins that could predict survival. Predictiveness curves were plotted for significant proteins for VPA response (p-value < 0.005) to show the survival probability vs. the protein expression percentiles. RESULTS: A total of 124 proteins were identified pre- vs. post-CRT that were differentially expressed between the cohorts who received CRT plus VPA and those who received CRT alone. Clinical factors did not confound the results, and distinct proteomic clustering in the VPA-treated population was identified. Time-dependent ROC curves for OS and PFS for landmark times of 20 months and 6 months, respectively, revealed AUC of 0.531, 0.756, 0.774 for OS and 0.535, 0.723, 0.806 for PFS for protein expression, clinical factors, and the combination of protein expression and clinical factors, respectively, indicating that the proteome can provide additional survival risk discrimination to that already provided by the standard clinical factors with a greater impact on PFS. Several proteins of interest were identified. Alterations in GALNT14 (increased) and CCL17 (decreased) (p = 0.003 and 0.003, respectively, FDR 0.198 for both) were associated with an improvement in both OS and PFS. The pre-CRT protein expression revealed 480 proteins predictive for OS and 212 for PFS (p < 0.05), of which 112 overlapped between OS and PFS. However, FDR-adjusted p values were high, with OS (the smallest p value of 0.586) and PFS (the smallest p value of 0.998). The protein PLCD3 had the lowest p-value (p = 0.002 and 0.0004 for OS and PFS, respectively), and its elevation prior to CRT predicted superior OS and PFS with VPA administration. Cancer hallmark genesets associated with proteomic alteration observed with the administration of VPA aligned with known signal transduction pathways of this agent in malignancy and non-malignancy settings, and GBM signaling, and included epithelial-mesenchymal transition, hedgehog signaling, Il6/JAK/STAT3, coagulation, NOTCH, apical junction, xenobiotic metabolism, and complement signaling. CONCLUSIONS: Differential alteration in proteomic expression pre- vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA. Using pre- vs. post-data, prognostic proteins emerged in the analysis. Using pre-CRT data, potentially predictive proteins were identified. The protein signals and hallmark gene sets associated with the alteration in the proteome identified between patients who received VPA and those who did not, align with known biological mechanisms of action of VPA and may allow for the identification of novel biomarkers associated with outcomes that can help advance the study of VPA in future prospective trials.

Lactate dehydrogenase D serves as a novel biomarker for prognosis and immune infiltration in lung adenocarcinoma.

BACKGROUND: Lung cancer is reported to be the leading cause of death in males and females, globally. Increasing evidence highlights the paramount importance of Lactate dehydrogenase D (LDHD) in different types of cancers, though it's role in lung adenocarcinoma (LUAD) is still inadequately explored. In this study, we aimed to investigate and determine the relationship between LDHD and LUAD. METHODS: The collection of the samples was guided by The Cancer Genome Atlas (TCGA) datasets and Gene Expression Omnibus (GEO). To ascertain various aspects around LDHD function, we analyzed different expression genes (DEGs), functional enrichment, and protein-protein interaction (PPI) networks. The predictive values for LDHD were collectively determined using the Kaplan-Meier method, Cox regression analysis, and a nomogram. Evaluation of the immune infiltration analysis was completed using Estimate and ssGSEA. The prediction of the immunotherapy response was based on TIDE and IPS. The LDHD expression levels in LUAD were validated through Western blot, qPCR, and immunohistochemistry methods. Wound healing and transwell assays were also performed to illustrate the aggressive features in LUAD cell lines. RESULTS: The results showed that LDHD was generally downregulated in LUAD patients, with the low LDHD group presenting a decline in OS, DSS, and PFI. Enriched pathways, which include pyruvate metabolism, central carbon metabolism, and oxidative phosphorylation were observed through KEGG analysis. It was also noted that the expression of LDHD expression was inversely related to immune cell infiltration and typical checkpoints. The high LDHD group's response to immunotherapy was remarkable, particularly in CTAL4 + /PD1- therapy. In vitro studies revealed that the overexpression of LDHD caused tumor migration and invasion to be suppressed. CONCLUSION: In conclusion, our study revealed that LDHD might be an effective predictor of prognosis and immune filtration, possibly leading to better choices for immunotherapy.

Microbial peptides activate tumour-infiltrating lymphocytes in glioblastoma.

Microbial organisms have key roles in numerous physiological processes in the human body and have recently been shown to modify the response to immune checkpoint inhibitors1,2. Here we aim to address the role of microbial organisms and their potential role in immune reactivity against glioblastoma. We demonstrate that HLA molecules of both glioblastoma tissues and tumour cell lines present bacteria-specific peptides. This finding prompted us to examine whether tumour-infiltrating lymphocytes (TILs) recognize tumour-derived bacterial peptides. Bacterial peptides eluted from HLA class II molecules are recognized by TILs, albeit very weakly. Using an unbiased antigen discovery approach to probe the specificity of a TIL CD4+ T cell clone, we show that it recognizes a broad spectrum of peptides from pathogenic bacteria, commensal gut microbiota and also glioblastoma-related tumour antigens. These peptides were also strongly stimulatory for bulk TILs and peripheral blood memory cells, which then respond to tumour-derived target peptides. Our data hint at how bacterial pathogens and bacterial gut microbiota can be involved in specific immune recognition of tumour antigens. The unbiased identification of microbial target antigens for TILs holds promise for future personalized tumour vaccination approaches.

Increased copy number of imprinted genes in the chromosomal region 20q11-q13.32 is associated with resistance to antitumor agents in cancer cell lines.

BACKGROUND: Parent of origin-specific allelic expression of imprinted genes is epigenetically controlled. In cancer, imprinted genes undergo both genomic and epigenomic alterations, including frequent copy number changes. We investigated whether copy number loss or gain of imprinted genes in cancer cell lines is associated with response to chemotherapy treatment. RESULTS: We analyzed 198 human imprinted genes including protein-coding genes and noncoding RNA genes using data from tumor cell lines from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer datasets. We examined whether copy number of the imprinted genes in 35 different genome locations was associated with response to cancer drug treatment. We also analyzed associations of pretreatment expression and DNA methylation of imprinted genes with drug response. Higher copy number of BLCAP, GNAS, NNAT, GNAS-AS1, HM13, MIR296, MIR298, and PSIMCT-1 in the chromosomal region 20q11-q13.32 was associated with resistance to multiple antitumor agents. Increased expression of BLCAP and HM13 was also associated with drug resistance, whereas higher methylation of gene regions of BLCAP, NNAT, SGK2, and GNAS was associated with drug sensitivity. While expression and methylation of imprinted genes in several other chromosomal regions was also associated with drug response and many imprinted genes in different chromosomal locations showed a considerable copy number variation, only imprinted genes at 20q11-q13.32 had a consistent association of their copy number with drug response. Copy number values among the imprinted genes in the 20q11-q13.32 region were strongly correlated. They were also correlated with the copy number of cancer-related non-imprinted genes MYBL2, AURKA, and ZNF217 in that chromosomal region. Expression of genes at 20q11-q13.32 was associated with ex vivo drug response in primary tumor samples from the Beat AML 1.0 acute myeloid leukemia patient cohort. Association of the increased copy number of the 20q11-q13.32 region with drug resistance may be complex and could involve multiple genes. CONCLUSIONS: Copy number of imprinted and non-imprinted genes in the chromosomal region 20q11-q13.32 was associated with cancer drug resistance. The genes in this chromosomal region may have a modulating effect on tumor response to chemotherapy.

Genome-wide profiling of retroviral DNA integration and its effect on clinical pre-infusion CAR T-cell products.

BACKGROUND: Clinical CAR T-cell therapy using integrating vector systems represents a promising approach for the treatment of hematological malignancies. Lentiviral and γ-retroviral vectors are the most commonly used vectors in the manufacturing process. However, the integration pattern of these viral vectors and subsequent effect on CAR T-cell products is still unclear. METHODS: We used a modified viral integration sites analysis (VISA) pipeline to evaluate viral integration events around the whole genome in pre-infusion CAR T-cell products. We compared the differences of integration pattern between lentiviral and γ-retroviral products. We also explored whether the integration sites correlated with clinical outcomes. RESULTS: We found that γ-retroviral vectors were more likely to insert than lentiviral vectors into promoter, untranslated, and exon regions, while lentiviral vector integration sites were more likely to occur in intron and intergenic regions. Some integration events affected gene expression at the transcriptional and post-transcriptional level. Moreover, γ-retroviral vectors showed a stronger impact on the host transcriptome. Analysis of individuals with different clinical outcomes revealed genes with differential enrichment of integration events. These genes may affect biological functions by interrupting amino acid sequences and generating abnormal proteins, instead of by affecting mRNA expression. These results suggest that vector integration is associated with CAR T-cell efficacy and clinical responses. CONCLUSION: We found differences in integration patterns, insertion hotspots and effects on gene expression vary between lentiviral and γ-retroviral vectors used in CAR T-cell products and established a foundation upon which we can conduct further analyses.

Discovery of pathway-independent protein signatures associated with clinical outcome in human cancer cohorts.

Proteomic data provide a direct readout of protein function, thus constituting an information-rich resource for prognostic and predictive modeling. However, protein array data may not fully capture pathway activity due to the limited number of molecules and incomplete pathway coverage compared to other high-throughput technologies. For the present study, our aim was to improve clinical outcome prediction compared to published pathway-dependent prognostic signatures for The Cancer Genome Atlas (TCGA) cohorts using the least absolute shrinkage and selection operator (LASSO). RPPA data is particularly well-suited to the LASSO due to the relatively low number of predictors compared to larger genomic data matrices. Our approach selected predictors regardless of their pathway membership and optimally combined their RPPA measurements into a weighted risk score. Performance was assessed and compared to that of the published signatures using two unbiased approaches: 1) 10 iterations of threefold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Here, we demonstrate strong stratification of 445 renal clear cell carcinoma tumors from The Cancer Genome Atlas (TCGA) into high and low risk groups using LASSO regression on RPPA data. Median cross-validated difference in 5-year overall survival was 32.8%, compared to 25.2% using a published receptor tyrosine kinase (RTK) prognostic signature (median hazard ratios of 3.3 and 2.4, respectively). Applicability and performance of our approach was demonstrated in three additional TCGA cohorts: ovarian serous cystadenocarcinoma (OVCA), sarcoma (SARC), and cutaneous melanoma (SKCM). The data-driven LASSO-based approach is versatile and well-suited for discovery of new protein/disease associations.

Fitness Promotion in a Jump Rope-Based Homework Intervention for Middle School Students: A Randomized Controlled Trial.

Physical activity (PA) homework offers a promising approach for students to be physically active after school. The current study aims to provide holistic insights into PA homework design and the effects of implementation in practice. In total, ninety-three middle school students were randomly assigned to a homework group (HG) or control group (CG). Participants in HG (n = 47) were requested to complete jump rope homework three times per week for 12 weeks, while their counterparts in CG attended one health education class every week. A homework sheet was used to provide instructions and record information for exercise behaviors during homework completion. Physical fitness tests were conducted to investigate the effects of the jump rope homework on the physical fitness of middle school students. After the intervention, participants in HG reported moderate to vigorous PA during jump rope exercise. The average duration for each practice was approximately 48 min. The returned homework sheets accounted for 86.88% of all homework assignments, indicating a good completion rate. Compared with their counterparts in CG, participants performing jump rope exercise indicated greater improvement in speed, endurance, power, and core muscular endurance. Jump rope homework strengthened physical fitness for middle school students, which provided a valuable addition to comprehensive school PA practice.

Pharmacogenomics of in vitro response of the NCI-60 cancer cell line panel to Indian natural products.

BACKGROUND: Indian natural products have been anecdotally used for cancer treatment but with limited efficacy. To better understand their mechanism, we examined the publicly available data for the activity of Indian natural products in the NCI-60 cell line panel. METHODS: We examined associations of molecular genomic features in the well-characterized NCI-60 cancer cell line panel with in vitro response to treatment with 75 compounds derived from Indian plant-based natural products. We analyzed expression measures for annotated transcripts, lncRNAs, and miRNAs, and protein-changing single nucleotide variants in cancer-related genes. We also examined the similarities between cancer cell line response to Indian natural products and response to reference anti-tumor compounds recorded in a U.S. National Cancer Institute (NCI) Developmental Therapeutics Program database. RESULTS: Hierarchical clustering based on cell line response measures identified clustering of Phyllanthus and cucurbitacin products with known anti-tumor agents with anti-mitotic mechanisms of action. Curcumin and curcuminoids mostly clustered together. We found associations of response to Indian natural products with expression of multiple genes, notably including SLC7A11 involved in solute transport and ATAD3A and ATAD3B encoding mitochondrial ATPase proteins, as well as significant associations with functional single nucleotide variants, including BRAF V600E. CONCLUSION: These findings suggest potential mechanisms of action and novel associations of in vitro response with gene expression and some cancer-related mutations that increase our understanding of these Indian natural products.

Identification of genomic signatures in bone marrow associated with clinical response of CD19 CAR T-cell therapy.

CD19 CAR T-cell immunotherapy is a breakthrough treatment for B cell malignancies, but relapse and lack of response remain a challenge. The bone marrow microenvironment is a key factor in therapy resistance, however, little research has been reported concerning the relationship between transcriptomic profile of bone marrow prior to lymphodepleting preconditioning and clinical response following CD19 CAR T-cell therapy. Here, we applied comprehensive bioinformatic methods (PCA, GO, GSEA, GSVA, PAM-tools) to identify clinical CD19 CAR T-cell remission-related genomic signatures. In patients achieving a complete response (CR) transcriptomic profiles of bone marrow prior to lymphodepletion showed genes mainly involved in T cell activation. The bone marrow of CR patients also showed a higher activity in early T cell function, chemokine, and interleukin signaling pathways. However, non-responding patients showed higher activity in cell cycle checkpoint pathways. In addition, a 14-gene signature was identified as a remission-marker. Our study indicated the indexes of the bone marrow microenvironment have a close relationship with clinical remission. Enhancing T cell activation pathways (chemokine, interleukin, etc.) in the bone marrow before CAR T-cell infusion may create a pro-inflammatory environment which improves the efficacy of CAR T-cell therapy.

Identifying Epstein-Barr virus peptide sequences associated with differential IgG antibody response.

BACKGROUND: Epstein-Barr virus (EBV) infection contributes to cancers in a fraction of seropositive individuals, but much remains to be learned about variation in EBV-directed humoral immunity in cancer-free adults. METHODS: A protein microarray was used to probe serum from 175 Taiwanese and 141 Northern European adults for immunoglobulin G (IgG) antibody responses to 115 different peptide sequences, representing protein segments or protein variants, from 45 EBV proteins. It was posited that this antibody-based approach could identify EBV peptide sequences representing immunodominant regions relevant for B-cell immunity. RESULTS: Analyses of 45 EBV proteins with multiple protein segments or variants printed on the array identified eight EBV peptide sequences that appear to play a role in immunogenicity. This included: (1) three proteins with segments/regions associated with IgG reactivity (BALF5, LMP1, LMP2A); and (2) five proteins with sequence variants/amino acid changes associated with IgG reactivity (BDLF4, EBNA3A, EBNA3B, EBNA-LP, LF1). CONCLUSION: This examination of IgG antibody responses against 115 EBV peptide sequences in 316 cancer-free adults represents an important step toward identifying specific EBV protein sequences that play a role in generating B-cell immunity in humans.

TPWshiny: an interactive R/Shiny app to explore cell line transcriptional responses to anti-cancer drugs.

SUMMARY: The NCI Transcriptional Pharmacodynamics Workbench (NCI TPW) is an extensive compilation of directly measured transcriptional responses to anti-cancer agents across the well-characterized NCI-60 cancer cell lines. The NCI TPW data are publicly available through a web interface that allows limited user interaction with the data. We developed 'TPWshiny' as a standalone, easy to install, R application to facilitate more interactive data exploration.With no programming skills required, TPWshiny provides an intuitive and comprehensive graphical interface to help researchers understand the response of tumor cell lines to 15 therapeutic agents. The data are presented in interactive scatter plots, heatmaps, time series and Venn diagrams. Data can be queried by drug concentration, time point, gene and tissue type. Researchers can download the data for further analysis. AVAILABILITY AND IMPLEMENTATION: Users can download the ready-to-use, self-extracting package for Windows or macOS, and R source code from the project website (https://brb.nci.nih.gov/TPWshiny/). TPWshiny documentation and additional information can be found on the project website.

TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository.

BACKGROUND: In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis. METHODS: In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis. RESULTS: Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data. CONCLUSION: We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples.

Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT): A Randomized Multicenter Phase II Trial.

This trial assessed the utility of applying tumor DNA sequencing to treatment selection for patients with advanced, refractory cancer and somatic mutations in one of four signaling pathways by comparing the efficacy of four study regimens that were either matched to the patient's aberrant pathway (experimental arm) or not matched to that pathway (control arm). MATERIALS AND METHODS: Adult patients with an actionable mutation of interest were randomly assigned 2:1 to receive either (1) a study regimen identified to target the aberrant pathway found in their tumor (veliparib with temozolomide or adavosertib with carboplatin [DNA repair pathway], everolimus [PI3K pathway], or trametinib [RAS/RAF/MEK pathway]), or (2) one of the same four regimens, but chosen from among those not targeting that pathway. RESULTS: Among 49 patients treated in the experimental arm, the objective response rate was 2% (95% CI, 0% to 10.9%). One of 20 patients (5%) in the experimental trametinib cohort had a partial response. There were no responses in the other cohorts. Although patients and physicians were blinded to the sequencing and random assignment results, a higher pretreatment dropout rate was observed in the control arm (22%) compared with the experimental arm (6%; P = .038), suggesting that some patients may have had prior tumor mutation profiling performed that led to a lack of participation in the control arm. CONCLUSION: Further investigation, better annotation of predictive biomarkers, and the development of more effective agents are necessary to inform treatment decisions in an era of precision cancer medicine. Increasing prevalence of tumor mutation profiling and preference for targeted therapy make it difficult to use a randomized phase II design to evaluate targeted therapy efficacy in an advanced disease setting.

MutSpliceDB: A database of splice sites variants with RNA-seq based evidence on effects on splicing.

Splice site variants may lead to transcript alterations, causing exons inclusion, exclusion, truncation, or intron retention. Interpreting the consequences of a specific splice site variant is not straightforward, especially if the variant is located outside of the canonical splice sites. We developed MutSpliceDB: https://brb.nci.nih.gov/splicing, a public resource to facilitate the interpretation of splice sites variants effects on splicing based on manually reviewed RNA-seq BAM files from samples with splice site variants.

Molecular genomic features associated with in vitro response of the NCI-60 cancer cell line panel to natural products.

Natural products remain a significant source of anticancer chemotherapeutics. The search for targeted drugs for cancer treatment includes consideration of natural products, which may provide new opportunities for antitumor cytotoxicity as single agents or in combination therapy. We examined the association of molecular genomic features in the well-characterized NCI-60 cancer cell line panel with in vitro response to treatment with 1302 small molecules which included natural products, semisynthetic natural product derivatives, and synthetic compounds based on a natural product pharmacophore from the Developmental Therapeutics Program of the US National Cancer Institute's database. These compounds were obtained from a variety of plant, marine, and microbial species. Molecular information utilized for the analysis included expression measures for 23059 annotated transcripts, lncRNAs, and miRNAs, and data on protein-changing single nucleotide variants in 211 cancer-related genes. We found associations of expression of multiple genes including SLFN11, CYP2J2, EPHX1, GPC1, ELF3, and MGMT involved in DNA damage repair, NOTCH family members, ABC and SLC transporters, and both mutations in tyrosine kinases and BRAF V600E with NCI-60 responses to specific categories of natural products. Hierarchical clustering identified groups of natural products, which correlated with a specific mechanism of action. Specifically, several natural product clusters were associated with SLFN11 gene expression, suggesting that potential action of these compounds may involve DNA damage. The associations between gene expression or genome alterations of functionally relevant genes with the response of cancer cells to natural products provide new information about potential mechanisms of action of these identified clusters of compounds with potentially similar biological effects. This information will assist in future drug discovery and in design of new targeted cancer chemotherapy agents.

SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Since the publication of the Society for Immunotherapy of Cancer's (SITC) original cancer immunotherapy biomarkers resource document, there have been remarkable breakthroughs in cancer immunotherapy, in particular the development and approval of immune checkpoint inhibitors, engineered cellular therapies, and tumor vaccines to unleash antitumor immune activity. The most notable feature of these breakthroughs is the achievement of durable clinical responses in some patients, enabling long-term survival. These durable responses have been noted in tumor types that were not previously considered immunotherapy-sensitive, suggesting that all patients with cancer may have the potential to benefit from immunotherapy. However, a persistent challenge in the field is the fact that only a minority of patients respond to immunotherapy, especially those therapies that rely on endogenous immune activation such as checkpoint inhibitors and vaccination due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, the development of robust biomarkers for each immunotherapy strategy, enabling rational patient selection and the design of precise combination therapies, is key for the continued success and improvement of immunotherapy. In this document, we summarize and update established biomarkers, guidelines, and regulatory considerations for clinical immune biomarker development, discuss well-known and novel technologies for biomarker discovery and validation, and provide tools and resources that can be used by the biomarker research community to facilitate the continued development of immuno-oncology and aid in the goal of durable responses in all patients.

HLA-DR15 Molecules Jointly Shape an Autoreactive T Cell Repertoire in Multiple Sclerosis.

The HLA-DR15 haplotype is the strongest genetic risk factor for multiple sclerosis (MS), but our understanding of how it contributes to MS is limited. Because autoreactive CD4+ T cells and B cells as antigen-presenting cells are involved in MS pathogenesis, we characterized the immunopeptidomes of the two HLA-DR15 allomorphs DR2a and DR2b of human primary B cells and monocytes, thymus, and MS brain tissue. Self-peptides from HLA-DR molecules, particularly from DR2a and DR2b themselves, are abundant on B cells and thymic antigen-presenting cells. Furthermore, we identified autoreactive CD4+ T cell clones that can cross-react with HLA-DR-derived self-peptides (HLA-DR-SPs), peptides from MS-associated foreign agents (Epstein-Barr virus and Akkermansia muciniphila), and autoantigens presented by DR2a and DR2b. Thus, both HLA-DR15 allomorphs jointly shape an autoreactive T cell repertoire by serving as antigen-presenting structures and epitope sources and by presenting the same foreign peptides and autoantigens to autoreactive CD4+ T cells in MS.